__ ,Ps -2337
POLICY RESEARCH WORKING PAPER 2337
Pollution Charges, Community pressure may be
as strong an incentive for
Community Pressure, industrial firms to control
and Abatement Cost of pollution in China as pollution
levies are.
Industrial Pollution in China
Hua Wang
The World Bank
Development Research Group
Infrastructure and Environment
May 2000
POLIcY RESEARCH NVORKING PAPER 2337
Summary findings
Wang evaluates the strength of the effect that community He creates a model and estimates implicit prices for
pressure and pollurion charges have on industrial pollution discharges from community pressure, which
pollution control in China and estimates the marginal are determined jointly by the explicit price, the pollution
cost of pollution abatement. He examines a well- levy. He finds that the implicit discharge price is at least
documented set of plant-level data, combined with as high as the explicit price. In other words, community
community-level data, to assess the impact of pollution pressure not only exists but may be as strong an incentive
charges and community pressure on industrial behavior as the pollution charge is for industrial firmns to control
in China. pollution in China.
He constructs and estimates an industrial organic Wang's modeling approach also provides a way to
water pollution discharge model for plants that violate estimate the marginal cost of pollution abatement. The
standards for pollution discharge, pay pollution charges, empirical results show that the current marginal cosr of
and are constantly under community pressure to further abatement is about twice the effective charge rate in
abate pollution. China.
This paper - a product of Infrastructure and Environment, Development Research Group - is part of a larger effort in
the group to study environmental regulation in developing countries. Copies of the paper are available free from the World
Bank, 1818 H Street NW, Washington, DC 20433. Please contactYasminD'Souza, room MC2-622, telephone 202-473-
1449, fax 202-522-3236, email address ydsouza@worldbank.org. Policy Research Working Papers are also posted on the
Web at www.woridbank.org/research/workingpapers. The author may be contacted at hwang1(aworldbank.org. May
2000. (27 pages)
The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas aboot
! development issues. An objective ofthe series is to get the findings out quickly, even ifthe presentations are less thani fully polished. The
papers carry the names of the authors and should he cited accordingly. The findings, interpretations, and conclusions expressed in this
paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executite Directors, or thye
countries they represent.
Produced by the Policy Research Dissemination Center
Pollution Charges, Community Pressure, and Abatement Cost
of Industrial Pollution in China'
Hua Wang
Development Research Group
World Bank
My sincere thanks to Dr. Jostein Nygard and other World Bank colleagues for their comments on an earlier draft of this
paper, and to Ms. Ping Yun for her excellent research assistance. Thanks also go to China State Environmental
Protection Administration (SEPA) and Chinese Research Academy of Environmental Sciences (CRAES) for
providing data necessary for this research exercise. Usual disclaimer applies. Corresponding address: Dr. Hua
Wang, MC2-626, 1818 H St., N. W., Washington, DC 20433, USA. Email: HWANGI@worldbank.org.
Pollution Charges, Community Pressure, and Abatement Cost
of Industrial Pollution in China
I. Introduction
This paper reports an empirical analysis of industrial water pollution discharge in China. A well
documented plant-level data set is examined and combined with a community-level data set, which
allows for a careful assessment of the impact of pollution charge instrument and community pressure
on industrial behavior in China. An industrial organic water pollution discharge model is constructed
and estimated for those plants which violate pollution discharge standards and pay pollution charges
and are constantly under pressure for further pollution abatement from the communities. The impacts
of pollution charge and community pressure are estimated and compared with each other. Also
reported in this paper are the demand function approach to marginal abatement cost estimation and
the empirical results of Chinese industries.
In literature, two recent empirical studies demonstrated the existence of informal regulation,
or community pressure, of industrial pollution. Using Indonesian data of plant-level organic water
pollution, Pargal and Wheeler (1996) tested and supported the informal regulation hypothesis that
communities are often able to negotiate with or otherwise informally pressure polluting plants in the
vicinity to clean up when formal regulatory mechanisms are absent or ineffective. With data on
industries in the United States, Pargal et al. (1997) provided support for the idea that community-
based pressure on plants to abate pollution exists even in the presence of formal regulation. Under
formal regulation, the government acts as an agent for the community. Frequently employed
regulatory instruments include both command-and-control instruments such as effluent discharge
3
standards and market-based instruments such as emissions charges. When formal regulations are
absent or weak, many communities have struck bargains for pollution abatement with local factories.
As pointed in Pargal et al. (1997), this community-based informal regulation may take many
different forms including demands for compensation by community groups, social ostracism of the
firm's employees, the threat of physical violence, boycotting the firm's products, and monitoring and
publicizing the firm's emissions. They may rely on the leverage provided by recourse to civil law or
pressure through politicians and local administrators, or religious leaders. When formal regulatory
standards and institutions exist, informal regulation can still play a significant role in providing
incentives for polluters to abate pollution. One tactic a community can use is simply reporting the
violation of legal standards. Another channel for informal regulation is to pressure regulators to
tighten local monitoring and enforcement.
While the existence of informal regulation has been empirically demonstrated, an important
issue remains of how strong the informal regulation is. While one can expect that informal regulation
may play an important role in pollution control where formal policy doesn't exist, the importance of
informal regulation could be lower in a relative sense where formal regulation is functioning. Studies
on the strength of community pressure, both in an absolute sense and in a relative sense with respect
to formal government pollution regulations, can help both for better understanding polluters'
behavior as well as for designing pollution control programs for communities and governments.
This paper provides an empirical estimation of community pressure on pollution discharges
in China where formal regulation on industrial pollution exists. The pressure is estimated as an
implicit price it provides for pollution discharges. This implicit price is jointly estimated by a
discharge demand function with an explicit price that the current Chinese pollution charge system
imposes for pollution discharges. In the estimation, the implicit price is instrumented with variables
including community economic status and pollution discharge situation. The estimated implicit price
is compared with the explicit price the government regulation provides. Estimation results show that
4
informal regulation on those firms which are violating effluent concentration standards is at least as
strong as the pollution charge instrument which is imposed on the violators in China.
With the same pollution discharge model, this study also provides an assessment of the
impact of China's pollution charge on industrial organic water pollution discharge. China's pollution
charge system has been widely implemented for about 20 years. Almost all of China's counties and
cities have implemented the levy system, and approximately 500,000 factories have been charged for
their emissions. Despite certain weaknesses in the pollution levy system, it remains by far the largest
application of a market-based regulatory instrument in the developing world. And in sheer
magnitude, the current Chinese system may be without peer in the world. However, this system was
not systematically evaluated until recently. With plant-level and province-level data, Wang and
Wheeler (1996 & 1999) did econometric analyses of levy system enforcement and plants' responses
to the variance in the effective levy rate. These analyses have shown that the local enforcement of the
levy system has been driven by local socio-economic and environmental status and that industrial
firms do respond to the levy rate changes. Due to data limitations, however, levy price indices
constructed in these studies did not match very well with the levy formula employed in practice, nor
well fit with economic theory in terms of the consistency of the demand variable and the price. This
prevented the econometric analyses from being a rigorous quantitative estimation of the price
elasticity of pollution discharge.
This study employs a data set with detailed information on levy collection. A discharge
function of organic water pollution - chemical oxygen demand (COD) can be constructed and
estimated with a marginal levy price of COD which matches both the economic theory and the levy
practice in China. An implicit price index for pollution discharge is also constructed and
instrumented in this estimation, which should be able to provide a more accurate estimation of the
price elasticity of COD discharge. Analyses conducted in this study show that the pollution charge is
only one part in the marginal penalty of pollution discharge in China. The levy price is about half of
5
the total discharge price which equals the marginal penalty. For a firm minimizing the total cost, the
marginal abatement cost should be equal to the total discharge price, which is about twice of the levy
price in China.
The estimation of the pollution discharge demand function in this study also provides a
unique estimation of marginal pollution abatement cost. Two empirical models have been previously
employed in estimating marginal pollution abatement cost. The total factor productivity approach
estimates a total cost function which combines both production cost and pollution control cost. The
marginal cost of pollution abatement can be derived by taking the derivatives of the total cost with
respect to a specific pollutant. This marginal cost estimation takes into consideration of pollution
reduction both in the production process and the end-of-pipe treatment. However this method has
been rarely used because of heavy data requirements. Another method that has been used is the end-
of-pipe treatment approach which estimates an end-of-pipe treatment cost function. A marginal
abatement cost can be estimated by taking derivatives of the abatement cost with respect to a
pollutant. This approach only considers the pollution abatement option with the end-of-pipe
treatment.
The demand function approach to marginal abatement cost estimation, employed in this
study, requires information on prices of pollution discharges. Just as the total factor productivity
approach, this approach can provide a correct estimation of industrial firms' pollution abatement
costs which takes into consideration both the production process and the end-of-pipe treatment. To
author's knowledge, this is the first empirical estimation of pollution abatement cost with a pollution
discharge function.
This paper is organized as follows. The next section provides further background information
about the pollution control practices of those Chinese industries which have to pay a uniquely
designed fee for pollution discharge and are also under constant pressure of other formal and
informal pollution control measures as well. Section III presents the model for pollution discharge
6
where firm characteristics, input prices, community pressure and formal regulation are identified as
the major determinants. Data and variable descriptions are presented in section IV, and section V
provides estimation results. Section VI concludes the paper.
II. Institutional Background
Chinese industry has been fast growing in the past two decades with an average annual increase rate
about 15%. While about 50% of the total value of output comes from those industries established
originally by farmers, which are mostly privately owned, a significant portion of the industry,
especially those large firms, are state-owned enterprises (SOEs). Those state-owned enterprises face
imperfect market competition. The prices of the outputs are partly regulated by the government even
though recent reforms have brought more autonomy to the SOEs. While plant managers' incomes are
more and more correlated with the economic performances of the plants and it is in most plant
managers' interests to maximize profits, firms are facing constraints additional to those set by the
market in their practices of minimizing the total costs. One example is the target of minimum values
of output set by the government for some plants.
There are a set of pollution control policy instruments applied to Chinese industries2. The
central government set up the general requirement of regulation according to the environmental laws,
and it has been the local governments' responsibility to enforce and improve the regulations set by
the central government. There are command-and-control approaches such as the requirement of
environmental impact assessments for new construction projects and the requirement of design,
construction and operation of pollution treatment facilities simultaneously with the construction or
expansion of industrial production facilities. After the production processes are in place, the emission
2 For a detailed review of China's pollution control system, see Sinkule and Ortolano (1995).
7
standards and effluent concentration standards apply. However, while the command-and-control
approaches are implemented, it is not illegal to violate those requirements. It is not until recently that
a firm or its manager can be prosecuted for violating environmental standards. If not polluting
extensively, firms may not be seriously penalized, even when violating abatement deadlines that are
sometimes issued by local environmental authorities.
To provide incentives for industrial firms to control pollution, the environmental regulators
have relied heavily on a market-based approach since the early 1980's. For more than a decade,
hundreds of thousands of firms have had to pay a fee if their discharges did not meet the discharge
standards3. The Chinese environmental protection law specifies that "in cases where the discharge of
pollutants exceeds the limit set by the state, a compensation fee shall be charged according to the
quantities and concentration of the pollutants released." In 1982 after three years experimentation,
China's State Council began nationwide implementation of pollution charges. Since then billions of
Renminbi (RMB) have been collected each year from hundreds of thousands of industrial polluters
for air pollution, water pollution, solid waste, and noise. In 1996, the system was implemented in
almost all counties and cities. A total of 4 billion RMB's ($1 = 8RMB) were collected from about
half a million industrial firms. Numbers are increasing each year.
There are some unique features associated with the charge system. For wastewater, this
system only imposes charges on the pollutants over the standard4, among which, only the pollutant
which violates the standard the most enters into the calculation of the total levy fee. In other words,
fees are calculated for each pollutant in a discharge stream and the polluter only needs to pay
whichever amount has the highest value among all the pollutants. The Chinese central government
3Most small industries in the remote rural areas have effectively escaped the levy due to the weak enforcement capacity of
local environmental protection agencies.
4After 1993, the government started charging for wastewater discharges whether they met discharge standards or not.
8
constructs a uniform fee schedule, however the implementation in different regions is not uniform5.
The levy collected is used to finance environmental institutional development, administration and
environmental projects and to subsidize firms' pollution control projects. If a firm, who pays levies to
the levy fund, decides to invest in pollution abatement, a maximum of 80% of the levy paid by the
firm can be used to subsidize the investment project proposed by the firm. To make the levy
collection effective, a schedule of penalties is also specified6. Penalties can not be used to subsidize
firm-level pollution control projects. Although studies have been conducted to reform the levy
system with most analysts recommending raising China's pollution charge rate (SEPA, 1998), few
empirical analyses have actually investigated polluters' response to the existing charges. In Wang
and Wheeler (1996), province-level data on water pollution was analyzed and it was determined that
China's levy system had been working much better than previously thought. Provincial variations in
the enforcement of the levy appear to reflect the local valuation of environmental damage and
community capacity to enforce local norms. The results suggest that province-level pollution
discharge intensities have been highly responsive to provincial levy variations. With a joint plant-
level and city-level data set, Wang and Wheeler (1999) have shown that pollution intensities of
Chinese industries have been significantly responsive to the levy system, and that citizens'
complaints on pollution can significantly affect the implementation of air pollution levy system.
While under formal regulation, Chinese industries are also constantly under pressure from
local communities for further pollution control. Cases are not scarce in China where citizens or
citizen groups fight with plants which are seriously polluting local watersheds or airsheds by directly
using violence or lawsuit. Chinese environmental authorities are also responding to a citizen
complaint program with which any citizen can write, call or visit the local office of environmental
authorities for any environmental issues. Responding to those complaints, environmental authorities
5For a detailed discussion, see Wang and Wheeler (1996 and 1999) and SEPA (1998).
9
investigate the issues mostly by doing field inspections. Issues are for the most part settled with
polluters' correcting the problems. Each year hundreds of thousands of complaints are received.
Studies have shown that these complaints have significantly increased the numbers of inspections
(Dasgupta et al. 2000) and increased the effective rate of pollution charge (Wang and Wheeler,
1999), and have contributed to pollution reduction especially for air (Dasgupta and Wheeler, 1996).
III. Model
Models estimated in this study can be derived directly from the general assumption that firms are
minimizing the total cost7. Assuming that C is the total cost of inputs that a firm spends on the
production process and the pollution treatment facilities. C is then a function of x, the total amount
of a certain residual or pollutant such as chemical oxygen demand (COD). The firm discharges x to
the environment and gets a penalty of F due to this discharge. F is also a function of x.
A firm minimizes the sum of total input costs (C) and total penalty (F) of pollution discharge
(x):
(1) minimize C(x)+F(x).
To solve for the optimization problem, the first order condition is:
(2) DC/ax + aF/ax =0.
The first term in the first order condition (2) is the cost reduction of an extra unit of pollution
discharge. Therefore, the marginal abatement cost (MAC) of x is,
(3) MAC = - AC/ax.
6 The penalty schedule is usually referred as "four small parts" in Chinese.
7 As discussed in last section, most Chinese industries face additional constraints while minimizing the total cost.
But for some firms during a certain period of time, the management objective might not be to minimize the
total cost. For these firms, the models developed in the following are invalid.
10
The second term in the first order condition (2) is the marginal penalty of pollution discharge,
which can also be defined as pollution discharge price P:
(4) P = aFax
When F is a linear function of x, P is a constant. The first order condition (2) prescribes that a
firm abates its pollution up to a point where the marginal abatement cost equals the marginal penalty
of pollution discharge. From (2), one can solve for a pollution discharge demand function given
discharge price P:
(5) x = f (P).
While the total penalty (F) of a pollution discharge x may include both a financial penalty,
such as paying a discharge fee, and other damages to the firm, such as reputation damages with law
suits, citizen complaints / demonstrations, and risk of being shut-down, etc., the pollution discharge
price P also has two parts: one corresponding to the explicit financial charges (P1) and another
corresponding to implicit damages to the firm (P2).
The marginal abatement cost function can be derived from equations from (2) to (5), as,
(6) MAC = f-'(x).
Therefore, a marginal abatement cost function (MAC) can be obtained by first estimating a pollution
discharge demand function (x = f(P)) and then taking an inverse of the demand function.
In this study, a COD discharge demand function will be empirically estimated for Chinese
industries which have to pay a price for COD discharges and are constantly under strong pressure
from local communities for further pollution reduction. To estimate equation (5) for COD, four sets
of variables or determinants need to be identified:
a) plant characteristics (f), which includes sector, output, ownership (for efficiency), vintage (for
technology), etc.;
11
b) market prices (m), which includes manufacturing wage, materials price, capital price, energy
price, stock price of the plant, etc.;
c) community characteristics (c), such as income, education, environmental quality, population,
etc.;
d) pollution regulation (r), including pollution charges, inspection, etc.;
Assume a simple functional form of COD discharge as follows:
(7) x = aP
where x is a parameter which is determined by plant characteristics (f) such as total value of output,
sector, ownership, etc., and market prices (m). That is,
(8) a = t(f, m).
,B is a parameter to be estimated, which is the price elasticity of pollution discharge. P is an
aggregate price for the discharge of pollution COD. Price P is a function of variables for pollution
regulation and community characteristics, i.e.,
(9) P = P(r, c).
With further assumptions on the functional form of P, such as,
(10) P=yr 1c62,
the relative contribution of different sets of variables to the variance of pollution discharge can be
estimated by substituting (10) into (7).
In the Chinese case, which will be presented in the following, the formal regulation is a charge
on pollution discharge, from which an explicit price, the effective charge rate or levy price, P1 can be
observed. Equation (10) becomes,
(11) P=yPIcK2.
12
The implicit pollution discharge price generated by community pressure, or non-levy price, P2, can
then be estimated by subtracting P1 from P; i.e.,
(12) P2=P-PI .
In estimation, y in equation (11) can be identified with an appropriate assumption such as the
minimum implicit price P2 is zero in a society. In this case, estimated P2 would be a lower bound of
the community pressure on pollution discharge.
IV. Data and Variables
A plant-level dataset of 1500 industrial firms in 1994, which was randomly selected from a nation-
wide random sample, was provided by China State Environmental Protection Administration for
conducting analyses of economics of industrial pollution control in China. All plants were under
close monitoring by state and local environmental authorities, and information about pollution and
production was well documented. Among the 1500 firms, effective levy prices can be estimated for
about 200 firms which discharged COD at a level above the COD discharge standards and paid
discharge levies for the part of COD discharge above standards. City-level data about average wage,
water pollution discharge concentration and population density in 1994 were collected from China
urban statistical yearbooks.
Table 1 lists the major variables used in the model. The dependent variable is the total COD
discharge of a plant. Plant characteristics include sector, state ownership, and value of output. For
sectors, paper, chemical, food, and textile are water pollution intensive sectors. Their impacts on
COD discharge are expected to be positive. State-owned plants are expected to be less efficient, so
the impact on COD discharge is expected to be positive. Value of output measures the scale of a
plant. COD discharge is expected to grow with output, and the effect on COD discharge is expected
13
to be positive. However, the elasticity of pollution with respect to value of output is expected to be
significantly less than one because of the scale economies.
For market input prices, the city-level average wage was available and can approximate for
the manufacturing wage. As an input price, wage should have a positive impact on COD discharge.
However, wage is also a measure of wealth. Empirical studies on informal regulation have shown
that wealth is positively correlated with the strength of informal regulation of pollution, and therefore
wage can also have a negative effect on COD discharge. So, there is not a prior expectation of the
sign of the variable wage. There is also a possibility that the wage is an endogenous variable because
high income people may move away from pollution intensive areas. However, it is not expected to be
a problem because population mobility was extremely low in China in 1994.
Input price information is also reflected in the model by a dummy variable "coast." In the
coastal areas of China, materials price, capital price, energy price as well as manufacturing wage are
all higher than in non-coastal areas. However, income, education and population density are also
higher in the coastal areas, which are most important determinants of strength of informnal regulation
according to previous empirical studies (Pargal and Wheeler, 1996; Wang and Wheeler, 1996).
Therefore the possible effect of the variable "coast" is ambiguous and it is an empirical issue.
Two more community variables in table 1 are population density and average water pollution
discharge concentration. Both of the variables are expected to have negative effects on COD
discharge. The higher the population density, the stronger the informal regulation of pollution. The
worse the overall water pollution, the higher the demand of water pollution control, and therefore
informal water pollution regulations should be stronger.
The explicit COD discharge price is defined as the total levy paid for the above-standard
COD discharge divided by the total COD discharged at a concentration level above the standard. It is
an observed marginal economic penalty of COD discharge. The impact of the levy price on total
COD discharge is expected to be negative. There is a possibility that the levy price is endogenous in
14
the COD model because there are cases observed in China where final levy collection is negotiated
with the plants. However, this problem is not expected to be serious in this study because the selected
plants were under close monitoring by state environmental authorities and it was not very likely for
them to be able to bargain with environmental authorities to reduce levy payments.
V. Results
5.1 Discharge Function Estimation
An econometric model is estimated with the data described above. Table 2 lists estimates of
8
coefficients . As expected, plant characteristics play a significant role in determining the COD
discharge. The elasticity of COD discharge with respect to value of output is about 0.63. The state
owned enterprises discharge more COD. Water pollution intensive sectors such as paper, textile, food
and chemical industries have significant, positive coefficients.
The COD levy price has a highly significant, negative impact on COD discharge. The
elasticity is close to -1. Dummy variable "coast" is found to be significant and negative in the COD
discharge equation. Due to multicollinearity between these community variables, other variables do
not show significance. However, when these community variables are included in the model
individually, they are all significantly negative, except variable log(wage). Since the primary purpose
of this analysis is to estimate relative importance of community pressure with respect to formal
pollution regulation, the insignificant community variables are included in the final analysis to
enhance the robustness of the estimation.
8 Stata Robust procedure was used to correct the possible White heterogeneity associated with cross-section data.
15
5.2 Levy and Non-levy Price
The empirical model estimated in table 2 is based on the models previously presented in section III.
Specifically, the price function of (10) is specified in this study as,
(10)' P = yPl*Q~lD62w63e&4*coast
Where P1 is the levy price; Q is the city-level COD discharge average concentration; D is population
density; W is city-level average wage; and coast is a dummy variable of 1 for plants locating in
coastal areas and 0 for locating in non-coastal areas. 61, 62, 63, and 64 are all positive parameters.
The parameter cc in model (7) is specified as,
(8)' a = aO*yYiW82e 03Coast+ 04 State + aSector
where variables W and coast reflect input prices for production and pollution abatement. 01, 02 and
03 should be positive. The econometric model estimated in this study is as,
(13) ln(x) - ln(a) + 3 ln(P)
= (ln(ao)+1 ln(y)) + 01 ln(Y) + 04 State + L co Sector + f3 ln(P1)
± (f 61) ln(Q) + (p 62) ln(D) + (3 63+04) ln(W) + (p 64+03) coast + error,
where , should be negative.
Because of the dual roles of variable W and coast for input prices and community pressure,
parameters associated with these two variables cannot be fully identified without further restrictions
on the parameters. Because the purpose of this estimation is to assess how significant community
pressure is on pollution control relative to the formal pollution regulation, an estimation of the lower
bound of community pressure is sufficient for this exercise.
In order to get a lower bound of the estimation for community pressure, following restrictions
are further imposed:
a. 03z=04=0;
16
b. y=l/min(Q5ID 2WB3eM*cost).
Restriction (a) underestimates 63 and 64, while restriction (b) imposes that the minimum of
community pressure on pollution abatement be zero. With restrictions (a) and (b), all parameters in
the model can be identified.
While assuming the minimum implicit price generated from market and community pressure
on COD discharge in the sample is zero, y is estimated to be about 2.7. The total COD discharge
price P is then estimated for each plant. Subtracting levy price P1 from the total price P, the non-levy
price P2 is then estimated. Table 3 provides the mean and the median estimation of levy, non-levy
and total prices, as well as the ratio of P2 to P1.
The estimation results in table 3 reveal that the non-levy price is almost equal to the levy
price in general. The levy price in the coastal areas is not significantly higher than in the interior
regions, while the non-levy price in the coastal areas is 2-3 times of the non-levy price in the non-
coastal areas. Therefore the total price is higher in the coastal areas. In coastal areas, non-levy price
is higher than the levy price. No significant difference is found in the total prices between the state
sector and non-state sector. However, in the non-state sector, the non-levy price is higher than the
levy price. While no significant difference can be found between the levy price and the non-levy
price with different industrial sectors and different scales of plants, paper industries are found to face
the lowest total marginal penalty of COD discharge and large plants are paying less for one more unit
of COD discharge.
No other formal regulation variable other than pollution levy is included in the model. For
those plants in the sample which were paying fees for their violations of the COD discharge
standards, it is not very likely that other formal policy instruments practiced in China would have
systematic impacts on the variance of COD discharge. Nevertheless, missing these instruments in the
17
model could cause an overestimation of the levy price if they are positively correlated with the levy
price.
5.3 Marginal Abatement Cost
The scale parameter cc in the discharge function (7) can be estimated as a function of value of output,
state and sector when parameter y is identified in the model (13) while restriction (a) is imposed.
Then marginal COD abatement cost can be estimated with the functional form,
(14) MAC = (X/a)-PM
With restriction (a), MAC is underestimated. Table 4 lists MAC estimates for plants with different
scales, and different sectors and at different levels of percent COD reduction from current discharge
levels. A plant at a medium level of output and COD discharge is selected from each plant category
to do the simulation.
In table 4, the paper industry can be found to be an outlier, with highest COD discharges but
lowest abatement costs at the current discharge level. While the marginal abatement cost with paper
industries can be higher than other sectors when they are at same levels of COD discharges, currently
it is clearly a correct strategy for China to focus more on paper industries in order to address the
organic water pollution problem.
VI. Conclusion and Discussion
This paper analyzes the relative strength of informal regulation when formal regulation is present.
Using Chinese data on plant-level organic water pollution from those industrial plants violating
discharging standards, the author estimated a pollution discharge demand model which includes
18
variables for both formal and informal regulation. The sample selected includes those plants which
discharge water pollution at a concentration level above the discharge standards set by environmental
authorities and which pay the government fees for those above-standard discharges. An effective
discharge price, the levy price, is then constructed and estimated for the model. Community variables
such as average wage, pollution status, population density, etc., which are associated with informal
regulation, are included in the model as well. The estimation results show that both formal regulation
and community variables are significant determinants of the water pollution discharge behavior. The
relative strength of informal regulation is the estimated with respect to formal regulation.
A conservative estimation of the strength of informal regulation show that it is at least as
strong as formal regulation. The marginal financial penalty of pollution discharge estimated in this
study is more or less reflecting the strength of formal regulation. However, the estimated non-levy
price is a lower bound estimation of the implicit price generated from community pressure on
pollution discharge. There are two reasons for it to be a lower bound. First, the market input price
effect is embedded in the non-levy price estimation. Because the input price effect on pollution
discharge is positive, the negative effect of non-levy price on pollution discharge should be smaller
than the negative effect caused by the community pressure. Secondly, the minimum non-levy price is
assumed to be zero while it should be positive given the fact that the pollution control effort is far
from being satisfied by the citizens in China.
In the literature, there are only few econometric studies on determinants of pollution
discharge at the plant level. Econometric estimation of pollution discharge demand with a well
constructed discharge price is even more scarce. With a well documented plant-level data set from
China, this is the first such study. Not only are the effects of a pollution charge system examined
quite rigorously, possible impacts of community variables are also jointly assessed. The study shows
that the Chinese pollution levy system has been quite effective in providing incentives at least for
those industries which are violating water pollution discharge standards to control pollution.
19
The strong impacts of community variables on an industry's discharge performance in China,
found in this study, may not stop functioning even when plants are in compliance with discharge
standards. As long as a community is dissatisfied with its pollution situation, the pressure from the
community would be expected to continue. This pressure can be either directly imposed on polluting
plants, or indirectly via government pollution control authorities through "formal" channels such as
the citizen pollution complaint program, found to affect regulators' efforts in monitoring and
enforcement of regulatory programs such as the pollution charge system (see Wang & Wheeler 1996
& 1999 and Dasgupta et al. 2000). A cost-effective strategy for promoting pollution regulation in
China can be to provide pollution information services to communities, given the status of economic
development in the communities.
The marginal cost estimation shows that the paper industries have highest COD discharges
but lowest abatement costs at the current discharge level. While the marginal abatement cost with
paper industries can be higher than other sectors when they are at the same levels of COD discharges,
currently it is clearly a cost-effective strategy for China to focus more on paper industries' pollution
abatement in order to address the industrial organic water pollution problem.. While they are close to
those estimates with engineering approaches conducted in China, the results of this study could be
the lower bounds of the true abatement costs due to that the input price effects are assumed to be zero
in the estimations.
It is also worthwhile to point out that the estimated levy price is only about half of the
estimated marginal abatement cost in this study. This should not be viewed as in conflict with the
conclusion, which can also be drawn from this study, that the Chinese pollution levy instrument is an
effective policy instrument. The reason is that there are other formal and informal regulations which
are jointly with the pollution levy system providing incentives for industrial firms to abate pollution.
In practice, an effective levy price should always be lower than a firm's marginal abatement cost as
20
long as there are other positive pressures for the firm to abatement pollution and the firm is to
minimize the total cost.
21
References:
Dasgupta, Susmita and D. Wheeler, 1997, "Citizen Complaints as Environmental Indicators:
Evidence from China," World Bank Policy Research Working Paper #1704.
Dasgupta, S., B. Laplante, N. Mamingi and H. Wang, 2000, "Local Enforcement of Environmental
Regulation in China: the Role of Inspection and complaint," World Bank Policy Research Working
Paper (forthcoming).
Dasgupta, S., M. Huq, D. Wheeler and C.H. Zhang, 1996, "Water Pollution Abatement by Chinese
Industry: Cost Estimates and Policy Implications," World Bank Policy Research Working Paper
#1630.
Pargal, Sheoli & David Wheeler, 1996, "Informal Environmental Regulations in Developing
Countries," Journal of Political Economy, vol. 104, no. 6.
Pargal, Sheoli, H. Hettige, M. Singh and D. Wheeler, 1997, "Formal and informal regulation of
industrial pollution: comparative evidence from Indonesia and the United States," World Bank Policy
Research Working Paper # 1797.
SEPA (China State Environmental Protection Administration), 1998, Proceedings of the
International Workshop on the Reform of China Pollution Levy System, China Environmental
Sciences Press, January.
22
Sinkule, J. Barbara and Leonard Ortolanio, 1995, Implementing Environmental Policy in China,
Praeger Publishers, 1995.
Wang, Hua & David Wheeler, 1996, "Pricing Industrial Pollution in China: An Econometric
Analysis of the Levy System," World Bank Policy Research Working Paper #1644.
Wang, Hua & David Wheeler, 1999, "Endogenous Enforcement and Effectiveness of China's
Pollution Levy System," World Bank Policy Working Paper (forthcoming), presented in the
workshop "Market-Based Environmental Instruments" sponsored by the Association of
Environmental and Resource Economists and Harvard University, July, 1999.
23
Table 1. Variable Description
Variable name Definition Mean Variance
COD Total COD discharge 248.2 942.6
(10,000 ton)
OUTPUT total value of output 25746 91304
(10,000 yuan)
STATE Dummy for state-owned .71 .46
firms
PRICE total levy on COD over- 700 855
standard discharge / total
over-standard COD
discharge: yuan / ton
WAGE average wage of the city 3869.9 1208.5
where the firm locates
CODCON average COD discharge 341.5 177.4
concentration of the region
POPDEN Population density (lIKm2) 1604 1340
CHEMICAL Dummy for chemical .14 .34
industry
DRUG Dummy for drug industry .15 .36
FOOD Dummy for food industry .22 .42
PAPER Dummy for paper industry .14 .34
TEXTILE Dummy for textile industry .17 .38
24
Table 2: Discharge Function Estimation
Dependent variable: Log(COD)
Full Model Reduced Model
Log(OUTPUT) .625*** .614***
(9.31) (9.34)
STATE .407* .387*
(1.68) (1.65)
CHEMICAL 1.110*** 1.106***
(3.07) (3.08)
DRUG .740** .768**
(2.10) (2.21)
FOOD .838*** .879***
(2.61) (2.75)
PAPER 2.462*** 2.512***
(6.48) (6.67)
TAEXTILE .622* .673**
(1.84) (1.99)
Log(PRICE) -.992*** -.984***
(-12.98) (-12.89)
Log(WAGE) .484
(0.87)
Log(CODCON) -.370 -.384*
(-1.41) (-1.75)
Log(POPDEN) -.183
(-1.45)
COASTAL -.545* -.417*
(-1.87) (-1.89)
Constant 10.892** 13.627**
(2.00) (8.54)
N 177 177
R2 0.76 0.75
F-value 38.21 45.50
t-statistics are included in parentheses under the estimated parameters. Asterisks indicate the associated significance
levels: * for .10; ** for .05; *** for .01.
25
Table 3: Levy and Non-levy Prices by Industries
(RMB yuan / ton)
P1 (levy price) P2 (non-levy price) Pl+P2 P2/P1
By average values
Whole sample 700.1 743.0 1443.1 1.06
Non-coastal 711.1 454.7 1165.8 0.64
Coastal 691.2 975.4 1666.7 1.41
Non-state 588.2 826.6 1414.8 1.41
state 746.7 708.2 1454.9 0.95
Chemical 864.3 934.7 1799.0 1.08
drug 559.5 656.1 1215.6 1.17
food 668.1 703.9 1372.1 1.05
paper 212.1 160.1 372.1 0.75
Textile 802.1 822.5 1624.6 1.03
large 630.4 695.8 1326.2 1.10
medium 737.9 808.8 1546.7 1.10
small 728.6 704.8 1433.5 0.97
By Median values
Whole sample 414.26 399.5 813.7 0.96
Non-coastal 324.4 194.1 518.6 0.60
coastal 463.5 635.2 1098.7 1.37
Non-state 361.5 439.3 800.8 1.22
state 450.2 318.7 768.9 0.71
Chemical 420.1 473.0 893.1 1.13
drug 367.5 194.1 561.6 0.53
food 504.2 439.1 943.3 0.87
paper 91.5 83.3 174.8 0.91
textile 648.0 599.9 1247.8 0.93
large 246.4 225.3 558.0 0.91
medium 495.5 442.3 1019.4 0.89
small 458.5 404.2 859.0 0.88
26
Table 4: Marginal Abatement Costs (MAC)
Sector Scale # of Typical Typical Current MAC MAC MAC MAC MAC
firms in value COD MAC 10% 30% 50% 70% 90%
sample of discharge (yuan/ reduction reduction reduction reduction reduction
output (1 Ok ton)
(1 Ok tons)
yuan)
Total Large 58 25000 45 582.3 647.5 834.2 1171.1 1960.1 5933.5
Total Medium 73 4000 12 775.6 862.5 1111.2 1560.0 2610.9 7903.7
Total Small 49 900 2 1652.3 1837.5 2367.4 3323.5 5562.4 16838.2
Chemical Large 10 25000 75 454.3 505.2 650.9 913.8 1529.3 4629.4
Chemical Medium 10 3500 13 770.2 856.5 1103.5 1549.2 2592.8 7848.8
Chemical Small 4 1200 18 2879.8 3202.5 4126.0 5792.4 9694.5 29346.5
Drug Large 1 3 15000 58 293.9 326.9 421.2 591.2 989.5 2995.5
Drug Medium 10 4000 12 625.7 695.9 896.5 1258.6 2106.5 6376.6
Drug Small 4 1000 1.5 2125.6 2363.8 3045.5 4275.5 7155.7 21661.1
Food Large 8 30000 30 976.3 1085.7 1398.8 1963.7 3286.6 9949.0
Food Medium 17 5000 10 955.5 1062.6 1369.1 1922.0 3216.7 9737.5
Food Small 14 1000 3.5 998.7 1110.7 1430.9 2008.9 3362.2 10177.7
Paper Large 7 20000 1330 85.0 94.5 121.8 170.9 286.1 866.0
Paper Medium 10 3400 360 103.9 115.5 148.8 209.0 349.7 1058.7
Paper Small 7 1000 10 1781.2 1980.8 2552.0 3582.6 5996.1 18151.1
Textile Large 7 32000 22 1118.0 1243.3 1601.8 2248.7 3763.6 11392.8
Textile Medium 15 6000 6.5 1330.9 1480.1 1906.9 2677.0 4480.4 13562.9
extile Small 8 1400 2.2 1585.7 1763.4 2271.9 3189.5 5338.1 16159.2
27
Policy Research Working Paper Series
Contact
Title Author Date for paper
WPS2314 Technological Leadership and Beata K. Smarzynska April 2000 L. Tabada
Foreign Investors' Choice of 36896
Eintry Mode
WPS2315 Investment in Naturai Gas Pipelines Alejandro Jadresic April 2000 M. Salehi
in the Southern Cone of Latin America 37157
WPS2316 Distrubutional Outcomes of a Emanuela Galasso April 2000 P. Sader
Decentralized Welfare Program Martin Ravallion 33902
WPS2317 Trade Negotiations in the Presence of Keiko Kubota April 2000 L. Tabada
Network Externalities 36896
WPS231 8 Regulatory Reform, Competition, Mark A. Dutz April 2000 H. Sladovich
and Innovation: A Case Study of the Aydin Hayri 37698
Mexican Road Freign Industry Pablo Ibarra
WPS2319 Externalities and Production Gunnar S. Eskeland April 2000 H. Sladovich
Efficiency 37698
WPS2320 Does Mere Intense Cornpetition Lead Mark A. Dutz April 2000 H. Sladovich
to Higher Growth? Aydin Hayri 37698
WPS2321 Algorithms for Purchasing AIDS David Bishai April 2000 P. Sader
Vaccines Maria K. Lin 33902
C. W. B. Kiyonga
WPS2322 Self-Targeted Subsidies: The Richard H. Adams, Jr. April 2000 M. Coleridge-Taylor
Distributional Impact of the Egyptian 33704
Food Subsidy System
WPS2323 GlobalizalWon and Firms Financing Sergio Schmukler April 2000 E. Khine
Choices: Evidence frDm Emerging Esteban Vesperoni 37471
Econonnies
WPS2324 Give G,owth and Macroeconomic Brian Pinto Aprii 2000 H. Makarenko
Stability in Russia a Chance: Harden Vladimir Drebentsov 87832
Budgets by Eliminating Nonpayments Alexander Morozov
WPS2325 Banking Systems Around the Globe: James R. Barth April 2000 A. Yaptenco
Do Regulation and Ovvnership Affect Gerard Caprio, Jr. 31823
Perfcrmance and Stabiiity? Ross Levine
WPS2326 Hovw Lirban Concentration Affects Vernon Henderson April 2000 R. Yazigi
Economic Growth 37176
WPS2327 How the Republic of Korea's Financial Hong G. Min April 2000 P. Rathan-Raj
Structure Affects the Volatility of Jong-goo Park 33705
Four Asset Prices
Policy Research Working Paper Series
Contact
Title Author Date for paper
WPS2328 Social Transfers and Social Branko Milanovic April 2000 P. Sader
Assistance: An Empirical Analysis 33902
Using Latvian Household Survey Data
WPS2329 Improving Russia's Policy on Foreign Joel Bergsman May 2000 S. Craig
Direct Investment Harry G. Broadman 33160
Vladimir Drebentsov
WPS2330 Reducing Structural Dominance Harry G. Broadman May 2000 S. Craig
and Entry Barriers in Russian 33160
Industry
WPS2331 Competition, Corporate Governance, Harry G. Broadman May 2000 S. Craig
and Regulation in Central Asia: 33160
Uzbekistan's Structural Reform
Challenges
WPS2332 Financial Intermediary Distress in Paola Bongini May 2000 K. Labrie
the Republic of Korea: Small Is Giovanni Ferri 31001
Beautiful? Tae Soo Kang
WPS2333 Output Fluctuations in Latin America: Santiago Herrera May 2000 C. Palarca
What Explains the Recent Slowdown? Guillermo Perry 35328
Neile Quintero
WPS2334 Sex Workers and the Cost of Safe Vijayendra Rao May 2000 P. Sader
Sex: The Compensating Differential Indrani Gupta 33902
for Condom Use in Calcutta Smarajit Jana
WPS2335 Inflation and the Poor William Easterly May 2000 K. Labrie
Stanley Fischer 31001
WPS2336 Endogenous Enforcement and Hua Wang May 2000 Y. D'Souza
Effectiveness of China's Pollution David Wheeler 31449
Levy System